The most popular way to approach acoustic modeling is by using GMMs and MFCCs features [1]}, [2]}. For that reason, we set as baseline a 40-component GMM with the following input vector: 13 MFCCs, their deltas and delta-deltas. Moreover, DNNs have been found very useful for acoustic modeling [3]}, [4]}. Therefore, we propose an additional baseline: a DNN with 2 hidden layers followed by the 32-way softmax output layer – the input is set to be a log-mel spectrogram.
